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Economic Model for Gas-to-Power Project Capitalization in Developing Economy

Domain:

environment and energysocioeconomic

Record type:

paper
Creator:
Eph
Publisher:
SPE
Host:
ABSTRACT Gas-to-power electricity generation is an effective means by which oil and gas companies can move natural gas from both onshore and offshore reserves to the market. But due to the peculiar risks in developing regions like Nigeria, very little progress has been made in project capitalization in this energy sector. In this paper, an integrated economic model, made up of the basic cash flow, scenario, and risk simulation analyses has been developed. Authors of similar works stopped at this level. But here, based on projects’ risk profile, companies equipped with their risk aversion levels (1/investment capital initially) can obtain their risk-discounted profits and hence able to decide whether to invest or not. Decisions on best shares for capitalization can also be obtained in real time. A gas-to-power System of 5 MMscfd gas supply generating 14.4MW electricity was used as the test project. A 20-year project life was assumed. The results show that the natural gas supply aspect of the project is more profitable, earning US$1.84 per US$1.00 investment as against US$1.29 for the power generation. Profits of gas-to-power projects are mostly affected by changes in gas and electricity prices and supply reliabilities. For capitalization, investor A, an independent oil company with US$10 million investment capital can capitalize this project all alone (100% best share) obtaining a risk-discounted profit of US$4.34million. But investors B and C with US$2million and US$1.33million capital would have to share in 60%:40% project participation ratio earning US$1.55million and US$1.03million respectively to profitably capitalize the project. With this model, gas-to-power risks are proactively identified, evaluated and communicated for effective decision-making. Best shares for profitable project capitalization even in a developing economy like Nigeria are easily determined.

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doi.org

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